With only 49 days before this very long year comes to an end, we’re thrilled to announce the 2020 State of DevOps Report is finally here. We’re in our ninth year producing the State of DevOps Report; at this point, more than 35,000 technical professionals from around the world have contributed to this body of research, the longest-running and most widely referenced DevOps research in the industry.
I’m excited to announce the release of Puppet Enterprise 2019.8.3. This release builds on a number of important product enhancements based on customer feedback and delivers on the second phase of our highly requested Value Dashboard.
The 2019.8.2 release of Puppet Enterprise has added a significant improvement to code deployment by enabling Puppet modules to be downloaded in parallel instead of serially. This functionality was added to the upstream r10k project almost a year ago and has now been added to Puppet Enterprise Code Manager.
Puppet Plans were added in the 2019.2 release of Puppet Enterprise and Puppet Enterprise 2019.8.2 extends that functionality by adding support for scheduling Puppet Plans. This enables plans to be run at some point in the future or on a recurring schedule. Plans can be scheduled using the Puppet Enterprise console, Puppet Enterprise command line, or the Puppet Enterprise REST API. In this blog post we’ll walk through how to schedule a Puppet Plan in the Puppet Enterprise console.
The Docker infrastructure abstracts a lot of aspects of the creation of images and running them as containers, which we usually do not know about nor interact with. One of those aspects is the handling of the filesystem inside the container. This post is a case study on how we discovered that writing large amounts of data inside a container has side effects with memory caching. Initially, we thought that we had an issue with our source code, but this was never the case.
One of our most commonly requested integrations, Datadog cloud monitoring, was announced last week on the Datadog blog! Sleuth organizes your deployments into projects, which collect and organize key data from your code sources and their associated staging environments. This data consists of metrics and errors.
When we were building out our first UI at Speedscale we wanted to get something up and running quickly. Fortunately there are a ton of options of web frameworks that can be used to throw together a quick “hello world” kind of application. However, a SaaS application needs a lot more than just displaying data. It needs to handle user authentication, loading data from a backend API, displaying data in a variety of formats, etc.
DevOps practices, and the teams that implement them, are becoming increasingly critical to the value which any company provides its customers. This was the key message throughout a recent fireside chat between DevOps Institute Chief Ambassador Helen Beal and Moogsoft VP of Product and Design Adam Frank. A great paradox of the digital era is that, once written, software is invisible to those who write it.
Shipa, Corp., delivering a cloud native application management framework built to manage the full application lifecycle, today announced that it is open sourcing Ketch, Shipa’s deployment engine, under Apache License Version 2.0. This open source release is available on GitHub and follows the general availability launch of Shipa’s full application management framework in October.
On November 11, 2020, I had the pleasure of speaking with two incredible thought leaders in the DevOps space: Vivek Pandey, VP of Engineering at Shipa (https://www.shipa.io), and Patrick Deuley, Sr Product Manager at GitLab (https://www.gitlab.com). The topic of the discussion was “Monolith to Microservices,” and we covered three key areas: Starting out, Scaling and Developer Experience.
